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Implementation and Evaluation of a Web Ontology Storage based on Relation Analysis of OWL Elements and Query Patterns  

Jeong, Dong-Won (군산대학교 정보통계학과)
Choi, Myoung-Hoi (군산대학교 정보통계학과)
Jeong, Young-Sik (원광대학교 전기전자정보 공학부)
Han, Sung-Kook (원광대학교 전기전자정보 공학부)
Abstract
W3C has selected OWL as a standard for Web ontology description and a necessity of research on storage models that can store OWL ontologies effectively has been issued. Until now, relational model-based storage systems such as Jena, Sesame, and DLDB, have been developed, but there still remain several issues. Especially, they lead inefficient query processing performance. The structural problems of their low query processing performance are as follow: Jena has a simple structure which is not normalized and also stores most information in a single table. It exponentially decreases the performance because of comparison with unnecessary information for processing queries requiring join operations as well as simple search. The structures of storages(e.g., Sesame) have been completely normalized. Therefore it executes many join operations for query processing. The storages require many join operations to find simply a specific class. This paper proposes a storage model to resolve the problems that the query processing performance is decreased because of non-normalization or complete normalization of the existing storages. To achieve this goal, we analyze the problems of existing storage models as well as relations of OWL elements and query patterns. The proposed model, defined with the analysis results, provides an optimal normalized structure to minimize join operations or unnecessary information comparison. For the experiment of query processing performance, a LUBM data sets are used and query patterns are defined considering search targets and their hierarchical relations. In addition, this paper conducts experiments on correctness and completeness of query results to verify data loss of the proposed model, and the results are described. With the comparative evaluation results, our proposal showed a better performance than the existing storage models.
Keywords
Web Ontology; OWL; Storage; Query Response Time; Experiment; Evaluation;
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